Chevron Left
Back to Supervised Machine Learning: Regression and Classification

Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
24,409 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

Top reviews

FA

May 24, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

AD

Nov 23, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

Filter by:

1501 - 1525 of 4,803 Reviews for Supervised Machine Learning: Regression and Classification

By sagar l

•

Jan 3, 2023

truly build your fundamental and strengthen your both theoretical and practical knowledge on machine learning.

By Ashutosh S

•

Nov 9, 2022

I liked the lab part the most. I was able to understand how to implement models using python and its libraries

By Vu T

•

Jul 6, 2022

This course explained so many concepts I found difficult before starting it. 5/5. Thank you very much Coursera!

By Lars F

•

Jan 7, 2024

Great course, fantastic explanation to understand the algorithms and math behind regression and classification

By SUHAS Y ( G

•

Sep 15, 2023

IT WAS A AN INFORMATIVE COURSE UNDERSTANDING THE UNDERLYING THEORETICAL CONCEPTS OF ML WITH PRACTICAL SESSION.

By PCloud

•

Jul 21, 2023

It will be better if the practical labs are more challenging, or make the optional labs as hands on exercises.

By Umjetna I

•

Jun 28, 2023

It was much easier to understand than I thought it would be. I am a total beginner, yet I learned a lot there.

By Xiangnan Z

•

Jun 19, 2023

Andrew's explanation is very intuitive. It is easy to follow and understand the underlying idea of each topic.

By Abhijeet G

•

May 30, 2023

Very much helpful for beginners. Concepts are explained in a very detailed way. Also, all labs are beneficial.

By Liam W

•

Oct 11, 2022

Very helpful for someone wanting to understand the basics of machine learning without going too much in depth

By Nirmala R

•

Aug 17, 2022

Crisp videos and very nice illustrations! Implementing gradient descent really helps understand the algorithm.

By Tamara C

•

Nov 9, 2024

Las explicaciones del temario son sublimes, muy cercanas y visuales. La aplicación en Python, muy didáctica.

By Rola I

•

Sep 20, 2024

الدورة رائعة جدا و مفيدة ، لقد قمت بتعلم الكثير من الأشياء الجديدة و المفيدة في انشاء مشاريع ML ، شكرا رولا

By Darmen M

•

Jul 25, 2024

Very beginner friendly course. Experienced learners may view at 1.25-1.5x video speed. Overall, great course!

By Yu Y

•

Feb 10, 2024

A clear a thorough introduction to ML. Accessible to anyone with basics of mathmatics and programming or not!

By Leonid H

•

Dec 27, 2023

Excellent course for beginners, but you must have knowledge of engineering mathematics to facilitate learning

By Lucas D

•

Oct 14, 2023

Going from very simple ideas to advanced math concepts smoothly, I really enjoyed Andrew' pedagogical skills!

By Nina G

•

Aug 31, 2023

Very beginner friendly but with enough detail to keep those with more math and programming experience engaged

By Mashrur K

•

Jul 14, 2023

I rated this course a five, but only as a excellent pre-requisites (area) to other, even more advanced topics

By Nayan D

•

Mar 20, 2023

Really great course for diving into the world of Machine Learning. Excellent explanations. Great online labs.

By Aashit A

•

Dec 22, 2022

Andrew NG explained the machine learning concepts in very simple way, and further looking for the next course

By Hichem M

•

Oct 16, 2022

Excellent course that combines theoritical and practical aspects for regression and classification problems.

By Vasyl S

•

Oct 12, 2022

Great. Professional. Comprehensive. Inspiring.

I am also grateful for financial aid to complete this course.

By Aldo G

•

Jul 31, 2022

It is better than the previous version in octalab, keeping clear explanation and more interactive with Adrew.

By Luca C

•

Oct 25, 2024

One of the best courses I have ever taken throught my University career. A must for everyone in this domain.